Adaptive weighting of geophysical data types in joint inversion

Abstract

Method for adaptive weighting of geophysical data types in iterative joint inversion to speed convergence and aid escape from local minima of the penalty (objective) function. Two or more geophysical data sets ( 11 ) representing a region of interest are obtained, and are jointly inverted to infer models of the physical properties that affect the particular types of data used. The misfit for each data type is a weighted tem in the penalty function ( 13 ). The invention involves changing the weights ( 51 ) as the iteration cycles progress when the iteration convergence criteria are satisfied ( 15 ), to see if they remain satisfied ( 52 ) with the modified penalty function.

The invention claimed is: 
     
       1. A method for simultaneously determining a model for each of a plurality of physical properties of a subsurface region by iterative joint inversion of a plurality of corresponding geophysical data types, comprising using a computer to minimize a penalty function to determine model updates for a next iteration cycle, said penalty function containing a separate weighted term for each data type, wherein the penalty function weights are changed when one or more convergence criteria are satisfied. 
     
     
       2. The method of  claim 1 , wherein each iteration cycle of the joint inversion comprises simulating synthetic geophysical data using current models of the physical properties, and the penalty function measures degree of misfit between the synthetic data and corresponding measured data. 
     
     
       3. The method of  claim 2 , wherein the convergence criteria are based on a pre-selected tolerance for minimum change in misfit value, for a particular data type or for all data types combined, from one iteration to a next. 
     
     
       4. The method of  claim 2 , wherein when said one or more convergence criteria indicate convergence, the penalty function weights are changed in successive iterations to emphasize each data type in turn. 
     
     
       5. The method of  claim 4 , wherein an optimizer determines the model updates from the misfits, and wherein the iterative joint inversion is deemed finished when the optimizer can determine no update when each data type is emphasized in turn. 
     
     
       6. The method of  claim 4 , further comprising determining a particular data type causing said indicated convergence, and then deemphasizing that particular data type in one or more subsequent iterations. 
     
     
       7. The method of  claim 1 , wherein the convergence criteria are based on monitoring magnitude of model updates from one iteration to a next. 
     
     
       8. The method of  claim 1 , wherein each physical property model subdivides a volume of the subsurface region into discrete cells, and specifies a value of that physical property for each cell. 
     
     
       9. The method of  claim 1 , wherein the plurality of geophysical data types includes at least two of seismic data, electromagnetic data, gravity data, surface topography data, and surface displacement data. 
     
     
       10. The method of  claim 1 , wherein said plurality of physical properties includes at least two of fluid saturation, porosity, resistivity, seismic velocity, lithology, and density. 
     
     
       11. The method of  claim 1 , wherein the penalty function weights are changed in each iteration cycle in accordance with a predetermined scheme. 
     
     
       12. The method of  claim 1 , wherein the penalty function weights are changed at random in each iteration cycle. 
     
     
       13. The method of  claim 1 , wherein minimizing the penalty function comprises computing a gradient of the penalty function with respect to parameters of the model. 
     
     
       14. A computer program product, comprising a non-transitory computer usable medium having a computer readable program code embodied therein, said computer readable program code adapted to be executed to implement a method for simultaneously determining a model for each of a plurality of physical of a subsurface region by iterative joint inversion of a plurality of corresponding geophysical data types, said method comprising minimizing a penalty function to determine model updates for a next iteration cycle, said penalty function containing a separate weighted item for each data type, wherein the penalty function weights are changed when one or more convergence criteria are satisfied. 
     
     
       15. A method for producing hydrocarbons from a subsurface region, comprising:
 obtaining data resulting from at least two different types of geophysical surveys of the subsurface region; 
 processing the two or more different types of geophysical data by jointing inverting them to infer two or more corresponding physical property models, said joint inversion using an iterative method comprising minimizing a penalty function to determine model updates for a next iteration cycle, said penalty function containing a separate weighted term for each data type, wherein the penalty function weights are changed when one or more convergence criteria are satisfied; 
 using the physical property models resulting after convergence to determine hydrocarbon potential of the subsurface region; and 
 in response to a positive indication of hydrocarbon potential, drilling a well into the subsurface region and producing hydrocarbons from it.